diff --git a/.env.example b/.env.example
index 81e3aaf..016e580 100644
--- a/.env.example
+++ b/.env.example
@@ -31,6 +31,7 @@ STRATEGY=auto
 # BLUR_THRESHOLD=120.0        # Laplacian blur threshold; lower = accept more blur (default: 120.0)
 # MAX_AUTO_IMAGES=80          # Hard cap on auto-diversity selection (default: 80)
 # FRIGATE_SCORE_THRESHOLD=0.0 # Quality gate: remove images scoring below this after upload (0 = disabled; requires at least one prior run)
+# ENABLE_FRIGATE_SCORES=true  # Call Frigate's recognize endpoint after each upload to store quality scores (default: true; adds ~200ms per upload)
 
 # ── Caching & Models ──────────────────────────────────────────────────────────
 # FORCE_CPU=true              # Disable GPU, fall back to CPU
diff --git a/winnow/config.py b/winnow/config.py
index 6bd4dff..784b853 100644
--- a/winnow/config.py
+++ b/winnow/config.py
@@ -32,6 +32,7 @@ class _Config:
     MAX_AUTO_IMAGES: int = 80
     QUALITY_REPLACEMENT: bool = True
     FRIGATE_SCORE_THRESHOLD: float = 0.0
+    ENABLE_FRIGATE_SCORES: bool = True
 
     # People filtering
     MIN_FACE_COUNT: int = 0
@@ -64,6 +65,7 @@ class _Config:
         self.MAX_AUTO_IMAGES = int(os.getenv("MAX_AUTO_IMAGES", "80"))
         self.QUALITY_REPLACEMENT = os.getenv("QUALITY_REPLACEMENT", "true").lower() in ("true", "1", "yes")
         self.FRIGATE_SCORE_THRESHOLD = float(os.getenv("FRIGATE_SCORE_THRESHOLD", "0.0"))
+        self.ENABLE_FRIGATE_SCORES = os.getenv("ENABLE_FRIGATE_SCORES", "true").lower() in ("true", "1", "yes")
         self.FACE_MARGIN = float(os.getenv("FACE_MARGIN", "0.15"))
         self.USE_FULL_RESOLUTION = os.getenv("USE_FULL_RESOLUTION", "true").lower() in ("true", "1", "yes")
         self.ENABLE_FACE_ALIGNMENT = os.getenv("ENABLE_FACE_ALIGNMENT", "true").lower() in ("true", "1", "yes")
diff --git a/winnow/executor.py b/winnow/executor.py
index eeab846..1a84183 100644
--- a/winnow/executor.py
+++ b/winnow/executor.py
@@ -357,6 +357,17 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                 known_frigate_files_at_start: set[str] = get_tracked_frigate_filenames(name)
             else:
                 known_frigate_files_at_start: set[str] = set(_snapshot)
+                # Remove tracker mappings for files that no longer exist in Frigate
+                # (manually deleted, or cleaned up outside winnow). This corrects the
+                # effective_count so those slots are available for new uploads.
+                stale = get_tracked_frigate_filenames(name) - known_frigate_files_at_start
+                for stale_fn in stale:
+                    remove_frigate_file(name, stale_fn)
+                if stale:
+                    progress.console.print(
+                        f"  [dim]{name}: cleared {len(stale)} stale mapping(s)"
+                        " (file(s) no longer in Frigate)[/dim]"
+                    )
             effective_count = get_tracked_frigate_file_count(name)
             pre_run_count = effective_count
             quality_replacement = job.get("config", {}).get("quality_replacement", False)
@@ -367,6 +378,10 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                 effective_threshold = max(Config.FRIGATE_SCORE_THRESHOLD, _dynamic or 0.0)
                 if _dynamic is not None and _dynamic > Config.FRIGATE_SCORE_THRESHOLD:
                     logger.debug(f"{name}: dynamic Frigate score threshold {_dynamic:.3f}")
+                if pre_run_count == 0:
+                    progress.console.print(
+                        f"  [dim]{name}: first run — quality gate will apply from the next run[/dim]"
+                    )
             else:
                 effective_threshold = 0.0
             actually_uploaded: list[tuple[str, str | None]] = []
@@ -397,7 +412,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
                         progress.console.print(f"    [dim]⏭  {fname}: at cap, quality replacement disabled[/dim]")
                         progress.advance(upload_task)
                         continue
-                    using_fscore = has_frigate_scores(name)
+                    using_fscore = has_frigate_scores(name) and Config.ENABLE_FRIGATE_SCORES
                     if using_fscore:
                         candidate_score = recognize_face(fpath)
                         if candidate_score is None:
@@ -458,7 +473,7 @@ def upload_to_frigate(jobs: list[dict]) -> None:
 
                             asset_id = asset_map.get(fname)
                             if asset_id:
-                                post_fscore = recognize_face(fpath)
+                                post_fscore = recognize_face(fpath) if Config.ENABLE_FRIGATE_SCORES else None
                                 mark_uploaded(
                                     asset_id,
                                     person_name=name,